The use of big data analytics to predict the foreign exchange rate based on public media: A machine-learning experiment

Tsaih, Rua‐Huan; Kuo, Biing-Shen; Lin, Tzu-Hsiang; Hsu, Che-Chuan

doi:10.1109/mitp.2018.021921649

Cited by 12 publications

(3 citation statements)

References 8 publications

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“…In order to meet the needs of modern intelligent manufacturing enterprises for high-tech talents and to solve the problems of low experimental efficiency and no data in BD in the original training teaching [5,6], it is urgent to build a training platform based on the combination of BD and virtual reality to cope with these problems and challenges [7]. In order to better collect and share educational BD, a vocational education BD technical training platform was built, the collection and sharing of educational BD on one platform were concentrated, and at the same time, online learning, education prediction, policy making, and other related functions were integrated into this platform; on the one hand, the construction of "smart education" was accelerated, and on the other hand, the transmission and sharing of educational resources were promoted, the utilization rate of educational resources was improved, and education was promoted to be more equitable.…”

Section: Introductionmentioning

confidence: 99%

Construction of Big Data Technology Training Environment for Vocational Education Based on Edge Computing Technology

Cui

2022

Wireless Communications and Mobile Computing

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With the rapid growth of the BD (big data) industry, many universities are focusing their professional development and expansion efforts on cultivating talent in related industries as well as building and developing big data disciplines. The BD technical training platform of vocational education based on IPE (Integration of Production and Education) is built in this paper, and the agreement signing, process management, effectiveness evaluation, big data analysis, and statistics of the integration of production and education are realized using edge computing technology, providing a solution for the informatization development of the integration of production and education. The access sequence was discovered among some knowledge points, as well as the sequence of knowledge points frequently viewed by students, and the teaching platform adjusts the content of web pages based on these rules to better provide personalized services for users.

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Section: Introductionmentioning

confidence: 99%

Construction of Big Data Technology Training Environment for Vocational Education Based on Edge Computing Technology

Cui

2022

Wireless Communications and Mobile Computing

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“…They find CNN-Bidirectional GRU to be the most effective method for this analysis. Yan et al [46] match lenders with borrowers and find that the random forest algorithm works better than the gradient boosting method, while Tsaih et al [13] use aspects of speech tagging along with other methods like word tokenization on time-series data and finally create a machine learning model to predict the currency exchange rate/forex. Konstantinidis et al [47] study the impact of social media news/sentiments on asset prices and market movement, while Ma R. et al ( 2017) perform a comparative analysis.…”

Section: Literature Reviewmentioning

confidence: 99%

Thematic Analysis of Big Data in Financial Institutions Using NLP Techniques with a Cloud Computing Perspective: A Systematic Literature Review

Sharma,

Bharathy,

Karimi

et al. 2023

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This literature review explores the existing work and practices in applying thematic analysis natural language processing techniques to financial data in cloud environments. This work aims to improve two of the five Vs of the big data system. We used the PRISMA approach (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) for the review. We analyzed the research papers published over the last 10 years about the topic in question using a keyword-based search and bibliometric analysis. The systematic literature review was conducted in multiple phases, and filters were applied to exclude papers based on the title and abstract initially, then based on the methodology/conclusion, and, finally, after reading the full text. The remaining papers were then considered and are discussed here. We found that automated data discovery methods can be augmented by applying an NLP-based thematic analysis on the financial data in cloud environments. This can help identify the correct classification/categorization and measure data quality for a sentiment analysis.

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“…Das et al (2018) proposed a hybrid forecasting model combining Empirical Mode Decomposition (EMD) and fast reduced Kernel Extreme Learning Machine (KELM) for exchange rate forecasting and trend analysis. To improve the prediction accuracy, Tsaih et al (2018) used big data and machine learning models to forecast the exchange rate. Influenced by the European debt crisis and COVID-19 epidemic, how exchange rate volatility is transmitted from one region or market to other regions or markets, that is, the spillover effect of exchange rate volatility, has attracted huge scholarly interest, causing "spillover" to edge onto the list of most frequently used keywords.…”

Section: Abstract Analysismentioning

confidence: 99%

30 years of exchange rate analysis and forecasting: A bibliometric review

Fang

Wei

Wang

2023

Journal of Economic Surveys

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Due to the strong nonlinearity and high complexity of foreign exchange rate data, how best to accurately analyze their trends and forecast them is regarded as a challenging research topic. While such research has developed rapidly and a large number of publications have appeared, few programmatic quantitative and qualitative overviews have been compiled in the field of exchange rate. By integrating bibliometric methods with network visualization based on CiteSpace software, this study analyzed 4999 publications of exchange rate research from the Web of Science (WoS) Core Collection database during 1992 to 2021. The study summarizes the major development in exchange rate determination since Meese‐Rogoff puzzle, from New Open‐Economy Macroeconomics (NOEM) and the Foreign Exchange Market Micro‐Structure Hypotheses, to determination model based on relationship between exchange rate and commodity price. Through the study's statistical analysis, co‐occurrence, co‐citation, and co‐keywords analysis, the influential authors, research institutions, countries and regions, journals, research hotspots, and future trends in the field of exchange rate are intellectually identified over the past 30 years. As a complement to existing literature, this paper provides theoretical and practical reference for researchers and practitioners in the field of exchange rate.

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The use of big data analytics to predict the foreign exchange rate based on public media: A machine-learning experiment

Cited by 12 publications

References 8 publications

Construction of Big Data Technology Training Environment for Vocational Education Based on Edge Computing Technology

Construction of Big Data Technology Training Environment for Vocational Education Based on Edge Computing Technology

Thematic Analysis of Big Data in Financial Institutions Using NLP Techniques with a Cloud Computing Perspective: A Systematic Literature Review

30 years of exchange rate analysis and forecasting: A bibliometric review

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